Biology subjects

Zeng, Z.

Publications and source records attributed to Zeng, Z..

At least 91 records · Page 5Linked to original sources

bioRxiv2022

Identify the origin and end cells and infer the trajectory of cellular fate automatically

Cellular state identification and trajectory inference enable reconstructions of cell fate dynamics from single-cell RNA sequencing. However, the identification of cell fate trajectories requires a large number of computational resources or known biological process, and lack a method to alleviate both of these deficiencies at the same time. Here, we present scLTNN, a method that automatically infers origin and end cell state from scRNA-seq data and calculates the developmental trajectory and differentiation direction of cells with only a few computational resources and time consummation. We apply scLTNN to disentangling subpopulation kinetics in CD8+ T cell, pancreatic endocrinogenesis, and the development of zebrafish embryos. scLTNN displays a strong trajectory inference ability cross-species. scLTNN features a modular design that can be flexibly extended to any scRNA-seq analysis task. The complete package is available online at https://github.com/Starlitnightly/scltnn.

bioinformatics↗

bioRxiv2022

MetaTiME: Meta-components of the Tumor Immune Microenvironment

Recent advances in single-cell RNA sequencing have revealed heterogeneous cell types and gene expression states in the non-cancerous cells in tumors. The integration of multiple scRNA-seq datasets across tumors can reveal common cell types and states in the tumor microenvironment (TME). We developed a data driven framework, MetaTiME, to overcome the limitations in resolution and consistency that result from manual labelling using known gene markers. Using millions of TME single cells, MetaTiME learns meta-components that encode independent components of gene expression observed across cancer types. The meta-components are biologically interpretable as cell types, cell states, and signaling activities. By projecting onto the MetaTiME space, we provide a tool to annotate cell states and signature continuums for TME scRNA-seq data. Leveraging epigenetics data, MetaTiME reveals critical transcriptional regulators for the cell states. Overall, MetaTiME learns data-driven meta-components that depict cellular states and gene regulators for tumor immunity and cancer immunotherapy.

genomics↗

bioRxiv2022

SOAR: a spatial transcriptomics analysis resource to model spatial variability and cell type interactions

Spatial transcriptomics provides researchers with a better understanding of gene expression within the tissue context. Although large volumes of spatial transcriptomics data have been generated, the lack of systematic curation and analysis makes data reuse challenging. Herein, we present Spatial transcriptOmics Analysis Resource (SOAR), a resource with an extensive, systematically compiled collection of spatial transcriptomics data across tissues, organs, and pathological conditions. SOAR is a comprehensive database with uniformly processed and annotated samples, facilitating future benchmark studies and method development. SOAR also offers multi-pronged analysis capability, including an integrative approach toward drug discovery that allows for efficient exploration of novel and targeted therapeutic uses for existing compounds.

bioinformatics↗

bioRxiv2022

The production of diverse brGDGTs by an Acidobacterium allows a direct test of temperature and pH controls on their distribution

Microbial lipid biomarkers preserved in geological archives can be used to explore past climate changes. Branched glycerol dialkyl glycerol tetraethers (brGDGTs) are unique bacterial biomarkers that have been used as molecular tools for the quantitative determination of terrestrial temperatures and the pH of depositional environments over a range of geological timescales. However, the exact biological source organisms - especially of the entire suite of brGDGTs found in the environment - remains unclear; by extension, so do the mechanisms that govern these proxies. Here, we identified a brGDGT-producing strain Candidatus Solibacter usitatus Ellin6076, by identifying archaeal tetraether synthase homologs in bacterial genomes. This strain synthesizes diverse brGDGTs, including regular C5-methylated and cyclic brGDGTs, and brGDGTs comprise up to 66% of the major lipids, far exceeding the proportions found in previous studies. The degree of C5-methylation in cultured strain Ellin6076 is primarily determined by temperature, whereas cyclization appears to be influenced by multiple factors. Consequently, culture-derived paleoclimate indices are in agreement with the global soil-derived MBT5ME (methylation index of C5-methyl brGDGTs) proxy for temperature but not the CBT5ME (cyclization index of C5-methyl brGDGTs) proxy for pH. Our findings provide important insights from a physiological perspective into the underlying mechanism of brGDGT-based proxies. Significance StatementBranched glycerol dialkyl glycerol tetraethers (brGDGTs) are biomarkers widely used for the quantitative estimation of past climatic changes due to their ubiquitous occurrence in the environment and the relationships between their distributions and temperature and pH. However, the ecophysiology of brGDGT-producing bacteria and the mechanistic basis for brGDGT-based climate proxies remain unknown. Here, we identify a brGDGT-producing Acidobacterium and present a physiological study of brGDGTs in response to cultivation variables, which provides pivotal insights into how brGDGT producers modulate methylation and cyclization under different culturing conditions. Our study represents a significant advancement in understanding the physiological role of lipid structures in microbial adaptation and helps us interpret the relationships between brGDGT-based proxies and environmental conditions of the geological environment.

microbiology↗

bioRxiv2022

Fate mapping melanoma persister cells through regression and into recurrent disease in adult zebrafish

Melanoma heterogeneity and plasticity underlie therapy resistance. Some tumour cells possess innate resistance, while others reprogramme during drug exposure and survive to form persister cells, a source of potential cancer cells for recurrent disease. Tracing individual melanoma cell populations through tumour regression and into recurrent disease remains largely unexplored, in part, because complex animal models are required for live imaging of cell populations over time. Here, we apply tamoxifen-inducible creERt2/loxP lineage tracing to a zebrafish model of MITF-dependent melanoma regression and recurrence to image and trace cell populations in vivo through disease stages. Using this strategy, we show that melanoma persister cells at the minimal residual disease site originate from the primary tumour. Next, we fate mapped rare MITF-independent persister cells and demonstrate that these cells directly contribute to progressive disease. Multiplex immunohistochemistry confirmed MITF-independent persister cells give rise to Mitfa+ cells in recurrent disease. Taken together, our work reveals a direct contribution of persister cell populations to recurrent disease, and provides a resource for lineage tracing methodology in adult zebrafish cancer models. Summary statementWe fate map melanoma cells from the primary tumour into a persister cell state and show that persister cells directly contribute to recurrent disease.

cancer biology↗

bioRxiv2022

CHDbase: A Comprehensive Knowledgebase for Congenital Heart Disease-related Genes and Clinical Manifestations

Congenital heart disease (CHD) is the most common cause of major birth defects, with a prevalence of 1%. Although an increasing number of studies reporting the etiology of CHD, the findings scattered throughout the literature are difficult to retrieve and utilize in research and clinical practice. We therefore developed CHDbase, an evidence-based knowledgebase with CHD-related genes and clinical manifestations manually curated from 1114 publications, linking 1124 susceptibility genes and 3591 variations to more than 300 CHD types and related syndromes. Metadata such as the information of each publication and the selected population and samples, the strategy of studies, and the major findings of study were integrated with each item of research record. We also integrated functional annotations through parsing ~50 databases/tools to facilitate the interpretation of these genes and variations in disease pathogenicity. We further prioritized the significance of these CHD-related genes with a gene interaction network approach, and extracted a core CHD sub-network with 163 genes. The clear genetic landscape of CHD enables the phenotype classification based on the shared genetic origin. Overall, CHDbase provides a comprehensive and freely available resource to study CHD susceptibility, supporting a wide range of users in the scientific and medical communities. CHDbase is accessible at http://chddb.fwgenetics.org/.

genetics↗

bioRxiv2021

A short prokaryotic argonaute cooperates with membrane effector to confer antiviral defense

Argonaute (Ago) proteins are widespread nucleic acid-guided enzymes that recognize targets through complementary base pairing. While in eukaryotes Agos are involved in RNA silencing, the functions of prokaryotic Agos (pAgos) remain largely unknown. In particular, a clade of truncated and catalytically inactive pAgos (short pAgos) lacks characterization. Here, we reveal that a short pAgo protein in Sulfolobus islandicus, together with its two genetically associated proteins, Aga1 and Aga2, provide robust antiviral protection via abortive infection. Aga2 is a membrane-associated toxic effector that binds anionic phospholipids via a basic pocket, which is essential for its cell killing ability. Ago and Aga1 form a stable complex that exhibits RNA-directed nucleic acid recognition ability and directly interacts with Aga2, pointing to an immune sensing mechanism. Together, our results highlight the cooperation between pAgos and their widespread associated proteins, suggesting an uncharted diversity of pAgo-derived immune systems that await to be discovered.

microbiology↗

bioRxiv2021

A deep learning-based multisite neuroimage harmonization framework established with traveling-subject dataset

The accumulation of multisite large-sample MRI datasets collected by large brain research projects in the last decade has provided a critical resource for understanding the neurobiological mechanisms underlying cognitive functions and brain disorders. However, the significant site effects, observed in the imaging data and their derived structural and functional features, has prevented the derivation of consistent findings across different studies. The development of harmonization methods that can effectively eliminate complex site effects while maintaining biological characteristics in neuroimaging data has become a vital and urgent requirement for multisite imaging studies. Here, we proposed a deep learning-based framework to harmonize imaging data from pairs of sites, in which site factors and brain features can be disentangled and encoded. We trained the proposed framework with a publicly available traveling-subject dataset from SRPBS and harmonized the gray matter volume maps from eight source sites to a target site. The proposed framework significantly eliminated inter-site differences in gray matter volume. The embedded encoders successfully captured both the abstract texture of site factors and the concrete brain features. Moreover, the proposed framework exhibited outstanding performance relative to conventional statistical harmonization methods in site effect removal, data distribution homogenization, and intra-subject similarity improvement. Together, the proposed method offers a powerful and interpretable deep learning-based harmonization framework for multisite neuroimaging data that could enhance reliability and reproducibility in multisite studies for brain development and brain disorders.

neuroscience↗

bioRxiv2021

Data-driven discovery of targets for bipotent anticancer drugs identifies Estrogen Related Receptor Alpha

Drugs that kill tumors through multiple mechanisms have potential for broad clinical benefits, with a reduced propensity to resistance. We developed BipotentR, a computational approach to find cancer-cell-specific regulators that simultaneously modulate tumor immunity and another oncogenic pathway. Using tumor metabolism as proof-of-principle, BipotentR identified 38 candidate immune-metabolic regulators by combining epigenomes with bulk and single-cell tumor transcriptomes from patients. Inhibition of top candidate ESRRA (Estrogen Related Receptor Alpha) killed tumors by direct effects on energy metabolism and two immune mechanisms: (i) cytokine induction, causing proinflammatory macrophage polarization (ii) antigen-presentation stimulation, recruiting CD8+T cells into tumors. ESRRA is activated in immune-suppressive and immunotherapy-resistant tumors of many types, suggesting broad clinical relevance. We also applied BipotentR to angiogenesis and growth-suppressor pathways, demonstrating a widely applicable approach to identify drug targets that act simultaneously through multiple mechanisms. BipotentR is publicly available at http://bipotentr.dfci.harvard.edu/. One-Sentence SummaryBipotentR identifies targets for bipotent anticancer drugs, as shown by the energy and immune effects of ESRRA inhibition.

cancer biology↗

bioRxiv2021

Machine learning modeling of protein-intrinsic features predicts tractability of targeted protein degradation

Targeted protein degradation (TPD) has rapidly emerged as a therapeutic modality to eliminate previously undruggable proteins by repurposing the cells endogenous protein degradation machinery. However, the susceptibility of proteins for targeting by TPD approaches, termed "degradability", is largely unknown. Recent systematic studies to map the degradable kinome have shown differences in degradation between kinases with similar drug-target engagement, suggesting yet unknown factors influencing degradability. We therefore developed a machine learning model, MAPD (Model-based Analysis of Protein Degradability), to predict degradability from protein features that encompass post-translational modifications, protein stability, protein expression and protein-protein interactions. MAPD shows accurate performance in predicting kinases that are degradable by TPD compounds (auPRC=0.759) and is likely generalizable to independent non-kinase proteins. We found five features with statistical significance to achieve optimal prediction, with ubiquitination potential being the most predictive. By structural modeling, we found that E2-accessible ubiquitination sites, but not lysine residues in general, are particularly associated with kinase degradability. Finally, we extended MAPD predictions to the entire proteome to find 964 disease-causing proteins, including 278 cancer genes, that may be tractable to TPD drug development.

bioinformatics↗

bioRxiv2021

Modular multilevel TMS device with wide output range and ultrabrief pulse capability for sound reduction

ObjectiveThis article presents a novel transcranial magnetic stimulation (TMS) pulse generator with a wide range of pulse shape, amplitude, and width. ApproachBased on a modular multilevel TMS (MM-TMS) topology we had proposed previously, we realized the first such device operating at full TMS energy levels. It consists of ten cascaded H-bridge modules, each implemented with insulated-gate bipolar transistors, enabling both novel high-amplitude ultrabrief pulses as well as pulses with conventional amplitude and duration. The MM-TMS device can output pulses including up to 21 voltage levels with a step size of up to 1100 V, allowing relatively flexible generation of various pulse waveforms and sequences. The circuit further allows charging the energy storage capacitor on each of the ten cascaded modules with a conventional TMS power supply. Main resultsThe MM-TMS device can output peak coil voltages and currents of 11 kV and 10 kA, respectively, enabling suprathreshold ultrabrief pulses (> 8.25 s active electric field phase). Further, the MM-TMS device can generate a wide range of near-rectangular monophasic and biphasic pulses, as well as more complex staircase-approximated sinusoidal, polyphasic, and amplitude-modulated pulses. At matched estimated stimulation strength, briefer pulses emit less sound, which could enable quieter TMS. Finally, the MM-TMS device can instantaneously increase or decrease the amplitude from one pulse to the next in discrete steps by adding or removing modules in series, which enables rapid pulse sequences and paired-pulse protocols with variable pulse shapes and amplitudes. SignificanceThe MM-TMS device allows unprecedented control of the pulse characteristics which could enable novel protocols and quieter pulses.

bioengineering↗

bioRxiv2021

Impact of bacterial microcompartment-dependent ethanolamine and propanediol metabolism on Listeria monocytogenes interactions with Caco-2 cells

Bacterial microcompartment (BMC) dependent ethanolamine (eut) and propanediol utilization (pdu) has recently been shown to stimulate anaerobic growth of Listeria monocytogenes. This metabolic repertoire conceivably contributes to the competitive fitness of L. monocytogenes in the human gastrointestinal (GI) tract, where these compounds become available following phospholipid degradation and mucus-derived rhamnose metabolism by commensal microbiota. Previous transcriptomics and mutant studies of eut and pdu L. monocytogenes suggested a possible role of eut and pdu BMC metabolism in transmission in foods and pathogenicity, but data on a potential role of L. monocytogenes interaction with human cells is currently absent. First, we ask which cellular systems are expressed in the activation of eut and pdu BMC metabolism and the extent to which these systems are conserved between the states. We find common and unique systems related to metabolic shifts, stress and virulence factors. Next, we hypothesize that these common and unique activated cellular systems contribute to a role in the interaction of L. monocytogenes interaction with human cells. We present evidence that metabolically primed L. monocytogenes with active eut and pdu BMCs, as confirmed by metabolic analysis, transmission electron microscopy and proteomics, show significantly enhanced translocation efficacy compared to non-induced cells in a trans-well assay using Caco-2 cells, while adhesion and invasion capacity was similar. Taken together, our results provide insights into the possible key cellular players that drive translocation efficacy upon eut and pdu BMC activation.

microbiology↗

bioRxiv2021

Impact of vitamin B12 on rhamnose metabolism, stress defense and in-vitro virulence of Listeria monocytogenes

Listeria monocytogenes is a facultative anaerobe which can cause a severe food-borne infection known as listeriosis. Rhamnose is a deoxyhexose sugar abundant in a range of environments, including the human intestine, and can be degraded by L. monocytogenes in aerobic and anaerobic conditions into lactate, acetate and 1,2-propanediol. Our previous study showed that addition of vitamin B12 stimulates anaerobic growth of L. monocytogenes on rhamnose due to the activation of bacterial microcompartment (BMC)-dependent 1,2-propanediol utilization with concomitant production of propionate and propanol. Notably, anaerobic propanediol metabolism has been linked to virulence of enteric pathogens including Salmonella spp. and L. monocytogenes. In this study we investigate the impact of B12 on aerobic and anerobic growth of L. monocytogenes on rhamnose, and observed growth stimulation and pdu BMC activation only in anaerobically grown cells with B12 added to the medium. Comparative Caco-2 virulence assays, showed that these pdu BMC induced cells have significantly higher translocation efficiency compared to aerobically grown cells (without and with added B12) and non-induced anaerobically grown cells, while adhesion and invasion capacity is similar for all cells. Comparative proteomics analysis showed specific and overlapping responses linked to metabolic shifts, activation of stress defense proteins and virulence factors, with RNA polymerase sigma factor SigL; teichoic acids export ATP-binding protein, TagH; DNA repair and protection proteins RadA and DPS; and glutathione synthase GshAB previously linked to activation of virulence response in L. monocytogenes, uniquely upregulated in anaerobically rhamnose grown pdu BMC induced cells. Our results shed new light into B12 impact on L. monocytogenes competitive fitness and virulence.

microbiology↗

bioRxiv2021

Based on the identification of tumor antigens and immune subtypes in renal clear cell carcinoma for mRNA vaccine development

BackgroundCancer vaccine based on mRNA is considered as a promising strategy and has become a new hot spot in cancer immunotherapy. However, its application to KIRC is not clear. A growing body of research has shown that immunotyping can reflect the comprehensive immune status and immune microenvironment of tumor, which is closely related to treatment response and vaccination potential. The aim of this study was to identify the potential antigens of KIRC for the development of anti-KIRC mRNA vaccines, and to further differentiate the immune subtypes of KIRC to construct an immune landscape for the selection of appropriate patients for vaccination. MethodsGene expression profiles and corresponding clinical information of 265 KIRC patients and RNA-seq data of 539 KIRC patients were retrieved from were collected from GEO and TCGA. cBioPortal was used to visualize and compare genetic alterations, while GEPIA2 was used to calculate the prognostic index of selected antigens. The relationship between the infiltration of antigen presenting cells and the expression of the identified antigen was visualized with TIMER, and consensus clustering analysis was used to determine the immune subtypes. Finally, the immune landscape of KIRC is visualized through the dimensionality reduction analysis based on graph learning. ResultsTwo tumor antigens associated with prognostic and antigen-presenting infiltrating cells were identified in KIRC, including LRP2, and DOCK8. KIRC patients were classified into six immune subtypes based on different molecular, cellular, and clinical characteristics. Patients with IS5 and IS6 tumors had an immune "hot" and immunosuppressive phenotype, which was associated with better survival compared to other subtypes, whereas patients with IS1-4 tumors had an immune "cold" phenotype, which was associated with a higher tumor mutation burden. In addition, the expression of immune checkpoints and immunogenic cell death modulators differed significantly in different immunosubtypes of tumors. Finally, the immune landscape of KIRC shows a high degree of heterogeneity across patients. ConclusionsLRP2 and FEM2 are potential KIRC antigens for mRNA vaccine development, and patients with immune subtypes IS1-4 are suitable for vaccination.

bioinformatics↗

bioRxiv2021

Tfap2b specifies an embryonic melanocyte stem cell population that retains adult multi-fate potential

Melanocytes, our pigment producing cells, are replenished from multiple stem cell niches in adult tissues. Although pigmentation traits are known risk-factors for melanoma, we know little about melanocyte stem cell (McSC) populations other than hair follicle McSCs, and lack key lineage markers with which to identify McSCs and study their function. Here, we discover that Tfap2b, and a select set of its target genes, specifies an McSC population at the dorsal root ganglia in zebrafish. Functionally, Tfap2b is required for only a few late-stage embryonic melanocytes, and instead is essential for McSC-dependent melanocyte regeneration. Fate- mapping data reveal that tfap2b-expressing McSCs have multi-fate potential, and are the cell-of- origin for large patches of adult melanocytes, and two other pigment cell types, iridophores and xanthophores. Hence, Tfap2b confers McSC identity in early development, thereby distinguishing McSCs from other neural crest and pigment cell lineages, and retains multi-fate potential in the adult zebrafish. HighlightsO_LITfap2b and its target genes specify McSCs with mixed pigment cell identities C_LIO_LIFunctional dependence on Tfap2b for melanocyte regeneration from the McSC C_LIO_LItfap2b specifies ErbB-dependent McSCs at the stem cell niche C_LIO_LIFate mapping reveals Tfap2b-McSCs have multi-fate potential for adult pigment cells C_LI

developmental biology↗

bioRxiv2021

3D-MASNet: 3D Mixed-scale Asymmetric Convolutional Segmentation Network for 6-month-old Infant Brain MR Images

Precise segmentation of infant brain MR images into gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) are essential for studying neuroanatomical hallmarks of early brain development. However, for 6-month-old infants, the extremely low-intensity contrast caused by inherent myelination hinders accurate tissue segmentation. Existing convolutional neural networks (CNNs) based segmentation models for this task generally employ single-scale symmetric convolutions, which are inefficient for encoding the isointense tissue boundaries in baby brain images. Here, we propose a 3D mixed-scale asymmetric convolutional segmentation network (3D-MASNet) framework for brain MR images of 6-month-old infants. We replaced the traditional convolutional layer of an existing to-be-trained network with a 3D mixed-scale convolution block consisting of asymmetric kernels (MixACB) during the training phase and then equivalently converted it into the original network. Five canonical CNN segmentation models were evaluated using both T1- and T2-weighted images of 23 6-month-old infants from iSeg-2019 datasets, which contained manual labels as ground truth. MixACB significantly enhanced the average accuracy of all five models and obtained the most considerable improvement in the fully convolutional network model (CC-3D-FCN) and the highest performance in the Dense U-Net model. This approach further obtained Dice coefficient accuracies of 0.931, 0.912, and 0.961 in GM, WM, and CSF, respectively, ranking first among 30 teams on the validation dataset of the iSeg-2019 Grand Challenge. Thus, the proposed 3D-MASNet can improve the accuracy of existing CNNs-based segmentation models as a plug-and-play solution that offers a promising technique for future infant brain MRI studies.

neuroscience↗

bioRxiv2021

Decoding the effects of synonymous variants

Synonymous single nucleotide variants (sSNVs) are common in the human genome but are often overlooked. However, sSNVs can have significant biological impact and may lead to disease. Existing computational methods for evaluating the effect of sSNVs suffer from the lack of gold-standard training/evaluation data and exhibit over-reliance on sequence conservation signals. We developed synVep (synonymous Variant effect predictor), a machine learning-based method that overcomes both of these limitations. Our training data was a combination of variants reported by gnomAD (observed) and those unreported, but possible in the human genome (generated). We used positive-unlabeled learning to purify the generated variant set of any likely unobservable variants. We then trained two sequential extreme gradient boosting models to identify subsets of the remaining variants putatively enriched and depleted in effect. Our method attained 90% precision/recall on a previously unseen set of variants. Furthermore, although synVep does not explicitly use conservation, its scores correlated with evolutionary distances between orthologs in cross-species variation analysis. synVep was also able to differentiate pathogenic vs. benign variants, as well as splice-site disrupting variants (SDV) vs. non-SDVs. Thus, synVep provides an important improvement in annotation of sSNVs, allowing users to focus on variants that most likely harbor effects.

bioinformatics↗

bioRxiv2021

Anaerobic growth of Listeria monocytogenes on rhamnose is stimulated by Vitamin B12 and bacterial microcompartment dependent 1,2-propanediol utilization

The food-borne pathogen Listeria monocytogenes is able to form proteinaceous organelles called bacterial microcompartments (BMCs) that optimize the utilization of substrates, such as 1,2-propanediol, and confer an anaerobic growth advantage. Rhamnose is a deoxyhexose sugar abundant in a range of environments including the human intestine, and can be degraded in anaerobic conditions into 1,2-propanediol, next to acetate and lactate. Rhamnose-derived 1,2-propanediol has been found to link with BMCs in a limited number of commensal human colonic species and some human pathogens such as Salmonella enterica, but the involvement of BMCs in rhamnose metabolism and potential physiological effects on L. monocytogenes are still unknown. In this study, we firstly test the effect of rhamnose uptake and utilization on anaerobic growth of L. monocytogenes EGDe without and with added vitamin B12, followed by metabolic analysis. We unveil that the vitamin B12-dependent activation of pdu stimulates metabolism and anaerobic growth of L. monocytogenes EGDe on rhamnose via 1,2-propanediol degradation into 1-propanol and propionate. Transmission electron microscopy of pdu-induced cells shows that BMCs are formed and additional proteomics experiments confirm expression of pdu BMC shell proteins and enzymes. Finally, we discuss physiological effects and energy efficiency of L. monocytogenes pdu BMC-driven anaerobic rhamnose metabolism and impact on competitive fitness in environments such as the human intestine.

microbiology↗